Microeukaryote community coalescence strengthens community stability and elevates diversity

Abstract Mixing of entire microbial communities represents a frequent, yet understudied phenomenon. Here, we mimicked estuarine condition in a microcosm experiment by mixing a freshwater river community with a brackish sea community and assessed the effects of both environmental and community coalescences induced by varying mixing processes on microeukaryotic communities. Signs of shifted community composition of coalesced communities towards the sea parent community suggest asymmetrical community coalescence outcome, which, in addition, was generally less impacted by environmental coalescence. Community stability, inferred from community cohesion, differed among river and sea parent communities, and increased following coalescence treatments. Generally, community coalescence increased alpha diversity and promoted competition from the introduction (or emergence) of additional (or rare) species. These competitive interactions in turn had community stabilizing effect as evidenced by the increased proportion of negative cohesion. The fate of microeukaryotes was influenced by mixing ratios and frequencies (i.e. one-time versus repeated coalescence). Namely, diatoms were negatively impacted by coalescence, while fungi, ciliates, and cercozoans were promoted to varying extents, depending on the mixing ratios of the parent communities. Our study suggests that the predictability of coalescence outcomes was greater when the sea parent community dominated the final community, and this predictability was further enhanced when communities collided repeatedly.


Introduction
Community coalescence is a complex phenomenon that involves the mixing of micr obial comm unities fr om pr e viousl y isolated environments (Rillig et al. 2015 ).Such mixing events comprise the movement and potential mixing of envir onments, r esulting in environmental coalescence, as well as the dispersal of micr obial comm unities termed biotic coalescence.Coalescence e v ents ar e expected to impose dual impacts on comm unities in the form of environmental filtering due to the altered environment following mixing, and community reorganization by the dynamic r earr angement of ecological inter actions , co vering competiti ve/facilitati ve interactions, species corecruitment, and trophic interactions (Rillig et al. 2015, Custer et al. 2023 ).Inter estingl y, colliding communities maintain some of these biotic interactions as intact, thus stabilizing the coalesced community (also known as network coherence) (Rillig et al. 2015 ).Hence, the likelihood of community establishment following coalescence can depend on biotic interaction types and the cohesiveness of taxa within the parent communities .T he recently developed 'cohesion' metric (Herren and McMahon 2017 ) quantifies the degree to which members of a community are connected and can be utilized to e v aluate its impact on community stability (see e.g.Hernandez et al. 2021 ).Higher fr action of positiv e cohesion indicates gr eater envir onmental sync hr on y and/or facilitativ e inter actions between taxa, which in turn results in a community with the potential for mutual downfall (Coyte et al. 2015 ).T his happens , for example, when the decreasing abundance of one species pulls others do wn and b y doing so, destabilizes the community via positivefeedback loops.In contrast, communities with a greater fraction of negative cohesion, attributed to competition and/or environmental filtering, tend to be more stable (e .g. ha ve low species turno ver o ver time) due to dampened positive feedback loops and reduced dependency (coupling) between species (Herren andMcMahon 2017 , Bier et al. 2022 ).Inferring community stability fr om comm unity coher ence , thus , r epr esents a promising avenue for understanding and predicting the outcome of community coalescence.Pr e vious works suggest that par ent comm unities with mor e facilitativ e inter actions contribute to a gr eater pr oportion of species in the final coalesced community due to their superior ability to deplete resources and resist invasions (Chang et al. 2021, Lechón-Alonso et al. 2021 ), especially when coalescence happens r epeatedl y (Lec hón-Alonso et al. 2021 , Song et al. 2021 ).T hus , the temporal scale on which coalescence events occur, for example, the frequency of invasion events (i.e.one-time versus repeated coalescence) have most likely plays a k e y role in determining the dominance of interaction type of a community network, and consequently, coalescence outcomes.
Coalescence e v ents ar e particularl y common in aquatic ecosystems as water bodies of different origins often mix at interfaces lik e ri ver-sea junctions (Rillig and Mansour 2017 ).Such estuary habitats pr esent c hallenging envir onments for micr obial comm unities in respect of salinity, oxygen levels, and nutrient concentr ations, whic h v ary gr eatl y not onl y spatiall y along the mixing zones but also tempor aril y as a result of the fluctuations that emerge due to hydrological features of river inflows and tidal intrusions (Wolanski et al. 2012, Lee et al. 2017, Mansour et al. 2018 ).This spatio-temporal environmental variability drives the development of diverse microbial communities, often characterized by protistan species maxima (Telesh et al. 2011 ).In estuaries, comm unities continuousl y coalesce and form a ne w set of populations with differ ent comm unity structur e and stability.Onl y micr obes that are able to adjust their osmoregulation and metabolic profiles (i.e.nutrient acquisition) and/or ele v ate their growth rates can survive these rapidly changing conditions (Bouvier and del Giorgio 2002, Balzano et al. 2015, Tee et al. 2021 ).Such river-sea mixing e v ents ar e particularl y common in the Baltic Sea, whic h is a shallow br ac kish sea c har acterized by lar ge riv er influence (Raudsepp et al. 2023 ) making it a perfect environment to study the process of whole-community mixing.Past works suggest that e v en low salinity en vironments , such as the Baltic Sea, impact riv er-tr ansported micr obes lac king ada ptability to saline conditions (Langenheder et al. 2003, Shen et al. 2018 ), shifting the final, mixed community to w ar ds that of the sea (Székely et al. 2013, Rocca et al. 2020, Song et al. 2022 ).
Although microeukaryotes play crucial roles in aquatic primary production and nutrient cycling via their roles in the food web, only a few studies have investigated the eukaryotic fraction of the microbial consortia along river-to-sea transects (Tee et al. 2021, Yang et al. 2021, Vass et al. 2022 ).Community coalescence and the mechanisms underlying its outcomes are nevertheless scarcely studied along river to sea transitions (Mansour et al. 2018 ).Ther efor e, we aimed to mimic estuarine condition in a microcosm experiment by mixing fr eshwater riv er comm unity with br ac kish sea comm unity and specificall y inv estigate whether the fate of microeukaryotes during community coalescence differ in response to varying mixing frequencies and ratios.
Her e, we addr ess two fundamental questions about comm unity coalescence: (i) Does mixing ratio define the outcomes of community coalescence?(ii) What effect does mixing frequency (one-time versus repeated coalescence) have on the final community composition?
Beginning with two microbial communities originating from a river and an offshore site in the Gulf of Bothnia, we inoculated each of them separately in their mixed environment to assess en vironmental coalescence .Community coalescence outcomes were also assessed after mixing them one-time or r epeatedl y at thr ee differ ent mixing r atios, v arying the initial r atio of the parent communities.We hypothesized that (a) it is possible to predict the outcome of community coalescence based on the applied mixing ratios and the individual environmental adaptive capabilities of the parent communities, and further, (b) that one-time coalescence is adv anta geous for competition-driv en (stable) comm unities, while repeated mixing of communities eventually results in facilitation-dominated communities, as suggested by Lechón-Alonso et al. ( 2021 ).

Sampling
The two microbiomes for our microcosm experiment were collected on 25 April 2022, from a subarctic coastal area of the Gulf of Bothnia, Sweden, which coincided with the diatom spring bloom.The fr eshwater riv er sample ( in situ temper atur e: 2.8 • C, pH: 5.6, salinity: 0.1 psu) originated from a coastal river, Ängerån (63 • 34 51.8 N; 19 • 50 07.0E).This river has a moderate ecological status and not heavily affected by anthropogenic influences, according to the Water Information System Sweden (viss .lansstyrelsen.se).T he brackish sea water ( in situ temper atur e: 5.2 • C, pH: 7.5, salinity: ∼4 psu) was collected from an offshore site (63 • 28 30.20 N; 19 • 50 5.85 E), ∼12 km from the mouth of the river Ängerån.River and sea samples were taken from the euphotic zone (integrated sample from 0 to 10 m depth, in the case of sea water) and transported to the laboratory in sterile containers .T he samples wer e pr efilter ed thr ough a 200-μm mesh to r emov e macr oor ganisms (i.e.mesozooplankton) and debris, and used immediately to set up the experiment.Total dissolved nitrogen (TDN) and phosphorus (TDP) were also measured, following standard analytical methods described in Hansen and Koroleff ( 1999 ).

Coalescence experiment
A 16-day long experiment was conducted, using parent communities pr epar ed fr om the riv er (R) and sea (S) samples (Fig. 1 ).These par ent comm unities (R and S) were then exposed to one-time (OC) or repeated (RC) coalescences in three river:sea mixing ratios (1:1, 1:2, and 2:1).
To avoid substantial chemical changes due to autoclaving, river (R m ) and sea (S m ) media was pr epar ed by sequentially filtration through GF/F filters (0.7 μm, Whatman) and then through sterile 0.2 μm 47 mm membrane filters (Pall Supor) in a laminar flow hood.Although this serial filtration was sufficient for elimination eukary otic cells, prokary otic cells w er e not completel y r emov ed and thus, axenic conditions were not ac hie v ed.Ho w e v er, onl y the sea medium experienced increased bacterial abundance by the end of our experiment (i.e .da y 16; Supplementary Fig. S1 ).
To assess the individual envir onmental ada ptiv e ca pabilities of the parent communities and estimate the effect of coalescence imposed solely by the abiotic envir onmental c hanges of the mixed media (i.e .en vir onmental coalescence), riv er and sea inoculum (80%; v/v) were incubated separately in blended native media (1:1 mixture of R m + S m ), hereafter R x and S x (i.e.envir onmental coalescence), r espectiv el y.For the comm unity coalescence tr eatments, the mixtur e of R m and S m were inoculated with river (R) and sea (S) parent communities (80%; v/v), according to the applied mixing ratios (e.g.OC 1:2 /RC 1:2 treatment consisted of 4 ml R m + 8 ml S m and 16 ml R + 32 ml S) in order to ac hie v e equall y dominated, sea-dominated or riv er-dominated conditions.
Every 4 days 20% sample volume of eac h OC micr ocosm was exchanged with the respective medium, following the initial mixing ratios .For this , each replicate 'A' of the communities received medium fr om r e plicate 'A'.Lik e wise, eac h r eplicate 'B' r eceiv ed medium from replicate 'B', and so on.Microcosms of RC treatment was exchanged with samples from the respective inoculum communities, instead of the filtered media, applying 20% (v/v) exc hange.Both the comm unity coalescence and the medium r eplacement were carried out in a laminar flow hood, using sterile disposable pipettes.
Figure 1.Ov ervie w of the experimental design.Pr efilter ed ( < 200 μm) water samples from two sites (river and sea) were collected to inoculate our microcosms .En vironmental coalescence: each parent community (R, S) was used to assess the potential environmental filtering effect of the mixed medium (river:sea = 1:1) on the unmixed parent communities (R x and S x ).Community coalescence: two different coalescence treatments (one-time-OC, and repeated-RC) were set up as follows.River and sea parent communities were mixed at three mixing ratios (1:1, 1:2, and 2:1, r espectiv el y) to create coalesced cultures.For the cultures exposed to environmental coalescence and the ones undergoing OC treatment, sterile-filtered ( < 0.2 μm) media (R m and S m ) were used during the course of the experiment (i.e.every fourth day) to refresh the parent communities.Cultures exposed to repeated coalescence (RC) received both parent communities mixed according to the corresponding coalescence treatment instead of the filtered media.All experimental treatments (each of 60 ml) consisted of five replicates.Parts of the figure were drawn by using pictures from Servier Medical Art.Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License ( https://cr eativ ecommons.org/licenses/by/3.0/).All treatments (60 ml each) with five replicates were maintained in sterile culture flasks with filter caps (Sarstedt, Nümbr ec ht, German y), r esulting in 60 cultures in total.The incubation was carried out at 10 • C with a photoperiod set to 17:7 h light:dark cycle to mimic ambient conditions (Andersson et al. 1994 ).Twice a day, the micr ocosms wer e mixed by gentl y shaking and r andoml y placed to minimize the potential biases of the differential light in the experiment room.

Monitoring microcosms during the experiment
Every 4 days subsamples (12 ml) from each culture flask were pipetted into sterile 15 ml tubes before the exchange of medium and/or parent community and processed as follows.
Bacterial abundances of glutaraldehyde-fixed samples (1 ml with 1% final concentration) were determined by flowcytometry (BD F ACSV erse instrument, BD Biosciences) using SYBR Green I (Invitrogen) staining dye (Marie et al. 1997 ).To assess and compare the growth of algae across microcosms, the subsamples were dark-adapted for at least 20 min and c hlor ophyll fluor escenceinduced dynamic curve was measured using AquaPen-C device (Photon Systems Instruments, Brno, Czec hia).The str ong corr elation between the integral area of chlorophyll fluorescence induction (OJIP) curve and chlorophyll-a content allo w ed us to estimate c hlor ophyll content of samples in a quic k, noninv asiv e way (Chen et al. 2021 ).The validity of this method was c hec ked by measuring the ethanol-extracted (95%) chlorophyll-a concentration of the initial water samples using spectr ofluor ometer and corr elated it with the integral area of the measured OJIP curves ( R 2 = 0.91).We acknowledge that this method has limitations , nevertheless , can be used to monitor our microcosms and to compare them among treatments.
At the end of the experiment (day 16) subsamples were filtered through 0.2-μm syringe filters and k e pt frozen until the measurement of chemical properties (e.g. total dissolved nutrients).TDN and TDP, were measured, following standard analytical methods described in Hansen and Koroleff ( 1999 ).The remaining sample v olumes w er e filter ed by v acuum filtr ation onto 0.2 μm 47 mm membr ane filters (P all Supor) and the filters wer e stor ed at -80 • C.

Community analysis by long-read amplicon sequencing
The DN A w as extr acted fr om the filters using the ZymoBIOMICS DNA Miniprep Kit (Zymo Researc h Cor p, CA, USA) following manufactur er's pr otocol.DNA extr acts wer e quantified with NanoDr op (ND-1000 Spectrophotometer).
Amplification was done using the V4_Balzano_F/D11_3143R primer pair (see, Supplementary Table S1 ) in order to amplify almost the whole ( ∼4.5 kb) eukaryotic rRNA operon (Latz et al. 2022 ), which allows better taxonomic classification.The PCR was performed according to Latz et al. ( 2022 ), using 20 ng template DNA.The barcoded PCR products were purified with 0.8 × of AMPure ma gnetic beads (Bec kmann) following the manufactur er's pr otocol.Ther eafter, the purified PCR pr oducts wer e quantified using the Qubit 1 × HS Assay Kit (ThermoFisher Scientific) and pooled in equimolar amounts.
18S, 28S rRNA genes (SSU and LSU) and the full length internal transcribed spacer (ITS) were extracted using ITSx (Bengtsson-Palme et al. 2013 ) and used in BLASTn search to assign taxonomy against the PR2 v4.14 database (Guillou et al. 2013 ), SILVA LSU v138.1 r efer ence database (Quast et al. 2012 ) and the UNITE + INSD v9.0 database (Abar enk ov et al. 2022 ), r espectiv el y, using BLAST + (v2.11.0 + ) and k ee ping hits with at least 80% identity.Results of the BLASTn sear ch w ere processed with phyloR ( https://github.com/ cparsania/ phyloR ) to k ee p top hits and to assign taxonomy le v els.Eac h oper ational taxonomic unit (OTU) was manually inspected by determining consensus classification down only to the le v el that could be r obustl y supported by at least two of the three r efer ence databases, using the 2 out of 3 rule (e.g. if an OTU classified as taxon A by two r efer ence databases but as taxon B by the third one, then taxon A is selected).Noneukaryotic consensus sequences and their corresponding OTUs were discarded from the OTU table ( n = 130).The taxonomic distribution of reads was visualized with Krona ( http:// sourceforge.net/projects/ krona ).

Da ta anal ysis
All statistical analyses and visualizations were conducted in R version 4.0.4(R Core Team 2021 ).Rarefaction was done using 4752 reads per sample, resulting in 461 O TUs .T he final OTU table and the corresponding taxonomy are available in Open Science Framework ( https:// osf.io/ sme36 ).Sample cov er a ge was assessed with the 'iNext' R pac ka ge (Hsieh et al. 2016 ), and found that community composition was sufficiently covered ( Supplementary Fig. S2 ).Differences in total dissolved nutrients (i.e.TDN and TDP) across inoculum sources and treatments were assessed by pairwise Wilcoxon rank-sum test with a Benjamini-Hoc hber g (BH) corrected significance cutoff of 0.05.Diversity analyses (alphadiversity and beta-diversity based on Bray-Curtis distance) were performed using the 'micr oeco' R pac ka ge (v.0.6.5)(Liu et al. 2021 ) and the results (i.e.nonmetric multidimensional scaling-NMDS) were plotted using 'ggplot' package (Wickham 2009 ).Difference in alpha diversity across inoculum sources and tr eatments wer e tested with ANOVA follo w ed b y Duncan's test ( P < .05)as a post hoc test.To test compositional differences between samples, pairwise permutational multivariate analysis of variance (PER-MANOVA, permutations: 999) was performed using the function pairwise.adonis in 'pairwiseAdonis' R pac ka ge (Arbizu 2019 ).

Community stability inferred from community cohesion
To estimate network coherence that impacts community stability, we first quantified the abundance-weighted pairwise correlations of e v ery OTU and used the r esulting positiv e and negativ e co-occurr ences separ atel y to calculate negative and positiv e comm unity cohesion, r espectiv el y, as pr oposed by Herr en and McMahon ( 2017 ).Cohesion is a metric that measures the degree of connectivity of each observed microbial community.Throughout this paper, we infer community stability from the absolute value of the ratio of negative and positive cohesion (negative: positive), as in Hernandez et al. ( 2021 ).This community stability metric takes < | 1 | values when communities have higher proportions of facilitation than competition, while values > | 1 | suggest competition-dominated communities, and thus, a community with mor e negativ e-feedbac k loops .T hr ough suc h negativ efeedback loops propagation of perturbations to the rest of the community is dampened, leading to greater overall community stability (Fontaine et al. 2011, Coyte et al. 2015 ).
Note that for the estimation of community stability, we used nonr ar efied dataset as suggested by Herren and McMahon ( 2017 ).Differ ences in comm unity stability acr oss inoculum sources and tr eatments wer e assessed by pairwise Wilcoxon r ank-sum test with a BH corrected significance cutoff of 0.05.

Evaluation of the environmental and biotic component of community coalescence
Changes in the r elativ e abundance of each OTU in the parent inoculum communities (i.e.R or S) compared to their abundance in mixed media of the environmental coalescence treatment (R x or S x ) were assessed by differential abundance analysis using Zi-coSeq (permutation: 999) (Yang and Chen 2022 ).Only taxa that wer e pr esent in both the par ent comm unity (i.e, R or S) and the corr esponding envir onmental coalescence tr eatments (i.e.R x or S x ), and that were not affected by the effect of environmental coalescence (i.e.sho w ed no significant ( p FDR.adj < 0.05) decrease in abundance in R x /S x compared to R/S) were selected for the subsequent analyses .T his ensured to filter out taxa affected by environmental coalescence (i.e.due to environmental filtering) and allo w ed us to assess the population-le v el dynamics attributed to the biotic component of community coalescence.
To e v aluate the outcome of suc h comm unity coalescence (i.e.biotic component of community coalescence), we quantified the extent of deviation between the observed coalesced communities and those expected according to a conserv ativ e mixing model as in Székely and Langenheder ( 2017 ) and Vass et al. ( 2021 ).For the expected communities we used the calculated OTU proportions from the two parent communities (R and S) with the applied mixing ratios and compared them with the observed OTU table (for detailed calculations consult Supplementary data Equation S1).
Thereafter, we calculated the Bray-Curtis similarities of the observed and expected coalesced communities .T he comparison of the Bray-Curtis similarities was used to indicate the predictability of coalescence outcomes and tested using t -tests.Specifically, no significant deviation ( P < .05)indicates that the observed community does not differ significantly from the expected one, suggesting predictable community coalescence.Differences between community coalescence treatments were assessed using a oneway ANOVA and a subsequent Tuk e y's HSD test.Ad ditionally, Bray-Curtis similarities between coalesced communities (i.e.OC and RC) and the corresponding parent communities (i.e.R and S) for the observed and expected data matrices were also calculated, separ atel y.Her e, a significantl y gr eater de viation between observ ed v ersus expected similarity ( P < .05)indicates that coalescence resulted in greater community divergence from the parent communities than expected.On the other hand, a significantly lo w er deviation ( P < .05)indicates a higher conv er gence to w ar ds the parent communities than expected, which could be a consequence of asymmetric coalescence outcome (i.e. the dominance of one parent community in the final, coalesced community).
To assess population dynamics in response to community coalescence, we used further differential abundance analyses (Zi-coSeq; permutation: 999) to detect OTUs with significant ( p FDR.adj < 0.05) increase or decrease in taxa abundances in the coalesced comm unities compar ed to their abundances in the par ent comm unities (R, S).Finall y, Kruskal-Wallis test (since the assumptions of tw o-w ay ANOVA w ere not met) w er e a pplied to r e v eal whether the different coalescence treatments, or mixing ratios, resulted in different total relative abundance of OTUs that increased or decreased after community coalescence.

Environmental condition of microcosms
Our parent (R, S) and coalesced communities (OC 1:1/1 : 2/2 : 1 and RC 1:1/1 : 2/2 : 1 ) sho w ed distinct c hemical and compositional pr operties.Total dissolved nutrients (i.e.TDN and TDP), as well as c hlor ophyll-a concentr ation-as a pr oxy of the biomass of primary producers-sho w ed v ariation acr oss micr ocosms ( Supplementary Figs S3 and S4 ).On av er a ge, sea medium (S m ) was nitrogen-poor (75.75 μg/l) compared to the river medium (R m : 451.24 μg/l) (Kruskal-Wallis: p adj < 0.05), and both had low levels of dissolved phosphorus (TDP; S m : 2.94 μg/l, R m : 3.2 μg/l).Microcosms exposed to environmental coalescence (i.e.R x , S x ) did not suggest nutrient-poor conditions by the end of the experiment, as they sho w ed similar TDP (3.36-3.72 μg/l) and greater .98 μg/l) values than those observed in filtered media (S m , R m ) ( Supplementary Fig. S3 ).Cultur es of comm unity coalescence treatments had even greater (Kruskal-Wallis: p adj < 0.05) availability of TDP (4.98 μg/l) than all the other microcosms (except sea inoculum), and their TDN le v els (292.69 μg/l, on aver-a ge) wer e intermediate between the le v els of R m and S m , showing significant differences (Kruskal-Wallis: p adj < 0.05) in relation to the applied mixing ratios .T he total dissolved nutrients, ho w ever, did not differ between one-time and repeated coalescence treatments.
Our inocula originated from oligotrophic ecosystems , hence , the ov er all observ ed low v alues of c hlor ophyll-a (0-4 μg/l) ar e not peculiar.Estimated biomass of primary producers was significantly higher (Tuk e y's HSD: P < .001) in sea (S: 3.12 μg/l) than in river (R: 0.78 μg/l) parent communities ( Supplementary Fig. S4 ).By the end of the experiment (i.e .da y 16), these parent communities also significantl y differ ed (Tuk e y's HSD: P < .001)fr om their r espectiv e comm unities that hav e been exposed to mixed media (S versus S x and R versus R x ).Interestingly, microcosms with sea inoculum r eac hed, on av er a ge, higher c hlor ophyll-a le v els when incubated in the mixed (S x : 2.66 μg/l) than in their original medium (S: 1.62 μg/l).In contr ast, riv er comm unity gr e w better in their original medium (R: 1.08 μg/l) compared to the mixed environment (R x : 0.32 μg/l).Biomass values in both coalescence frequency tr eatments conv er ged by day 16 (Tuk e y's HSD: P > .05),despite their initial differences (i.e .da y 4) (Tuk e y's HSD: P < .001;except between OC 1:1 and OC 2:1 communities) ( Supplementary Fig. S4 ).Here, we also found that algal biomass decreased over time in microcosms with greater sea microbiome dominance (i.e.mixing ratio of 1:2), in contrast to river inoculum-dominated microcosms wherein the biomass sho w ed an increased trend.

Community structure and stability
The NMDS of the microeukaryotic communities (Fig. 2 A) together with the pairwise PERMANOVA results sho w ed that the parent communities (S and R) and those exposed to environmental coalescence (S x and R x ), by mixing media with 1:1 ratio, compositionall y differ ed (pairwise PERMANOVA, P < .05),indicating the impact of environmental filtering.Communities exposed to differ ent comm unity coalescence tr eatments wer e also significantl y differ ent fr om eac h other (pairwise PERMANOVA, P < .05),except for OC 1:1 and RC 1:1 , as well as OC 1:1 and RC 1:2 .Although complete conv er gence to eac h of the par ent comm unity did not occur in any of these communities, the compositions of all community coalesced treatments shifted to w ar ds sea parent community (S).
When we inferred community stability from the ratio of negativ e v ersus positiv e comm unity cohesion, we found that communities had high proportions of positive cohesion (attributed to facilitativ e inter actions) in all cases (ratio of negati ve: positi ve cohesion   al. 2021 ).Ne v ertheless, sea par ent comm unities (S) wer e significantl y mor e stable (BH-corr ected Wilco xon test: P < .05)than ri ver par ent comm unities (R) (Fig. 2 B), and S community stability increased when they w ere gro wn in mixed media (S x and R x ).Similarl y, coalesced comm unities, OC tr eatments in particular, had gr eater comm unity stability (i.e.incr eased pr oportion of negativ e cohesion) than their r espectiv e par ent comm unities.Differ ences in mixing ratios had only an effect in the case of repeated coalescence treatments (Fig. 2 B), wherein community stability presented significant decr easing differ ence (BH-corr ected Wilcoxon test: P < .05) between RC 1:1 and RC 2:1 .

Compositional dynamics imposed by environmental and community coalescence
From a compositional point of view, sea inoculum r epr esented a diatom and dinoflagellate-dominated community ( Supplementary Fig. S7 ), while river inoculum was dominated by golden algae (e.g.Crysophyceae) and ciliates ( Supplementary Fig. S8 ).Differential abundance analysis revealed ten OTUs with > 10% prevalence (i.e .O TUs present in more than 10% of the samples) in the sea inoculum (mainly Oc hr ophyta and Dinofla gellata) and forty in the river inoculum (mainl y Oc hr ophyta).T hese O TUs wer e negativ el y affected ( p FDR.adj < 0.05) by environmental coalescence (in S x and R x ) ( Supplementary Figs S9 and S10 ).To assess the pure effect of biotic component of community coalescence in the subsequent analyses, we filtered out taxa that had been negativ el y impacted by environmental coalescence.Ther eafter, our differ ential abundance anal ysis r e v ealed numerous OTUs (pr e v alence > 10%) that decreased or increased in abundance .T he r elativ e abundances of these differ entiall y abundant taxonomic groups are presented in Fig. 3 .We found that mainly diatoms (e.g.Chaetoceros , Thalassiosira , and Skeletonema ) within the Oc hr oph yta ph ylum decreased in abundance (by 1.2% on av er a ge) after comm unity coalescence (Fig. 3 ).In contr ast, comm unity mixing r esulted in incr eased abundances of numerous microeukaryotes including fungi (with an increase of 3.3% on av er a ge, e.g.Ascomycota, Basidiomycota, and earl y-div er ging zoosporic fungi), ciliates ( + 2.8%) and other microeukaryotes [i.e.Cercozoa ( + 8.4%) and Katablepharidophyta (1.9%)] (Fig. 3 ).There wer e gener al tr ends showing that the r elativ e abundance of Cercozoa was higher ( + 3.5% on av er a ge) in the final (i.e.day 16) coalesced communities with more sea inoculum (i.e.mixing ratio of 1:2), while Ascom ycota, Basidiom ycota, Rozellom ycota, and Chlorophyta OTUs had greater relative abundances ( + 2.1% on aver a ge) in riv er dominated coalesced comm unities (i.e.mixing r atio of 2:1).
The total r elativ e abundances of the significantl y decr eased OTUs (selected based on the differential analysis) were significantly higher in repeated versus one-time coalescence treatments ( χ 2 = 23.77,P < .001).In contrast, coalescence frequency (one-time v ersus r epeated) had no effect on the r elativ e abundance of OTUs ( χ 2 = 2.19, P = .139)which maintained or significantly increased ( p FDR.adj < 0.05), following mixing.

Predictability of the biotic component of coalescence outcomes
The observed coalesced communities differed in all cases from their corresponding expected community compositions ( t -test: P < .001)and their predictability differed across coalescence treatments (ANOVA: F = 32.23,P < .0001)(Fig. 4 A).A clear pattern suggesting decreasing predictability of the coalesced communities with increasing ratio of river inoculum (i.e.predictability of river: sea mixing: 2:1 < 1:1 < 1:2) was found (Fig. 4 A).In addition, predictability was typically lo w er in communities exposed to onetime coalescence than in those subjected to repeated coalescence ( P < .05).
The observ ed Br ay-Curtis similarity between each coalesced community and its parent community was calculated and compared to the expected similarity (Fig. 4 B).This sho w ed that all communities had lo w er similarity to their parent communities than expected (ANOVA: F = 69.12,P < .001)(Fig. 4 B).Furthermore, communities that were either exposed to one-time coalescence treatment (i.e.empty triangles) or received higher proportion of river inoculum (i.e.y ello w triangles) tended to div er ge e v en mor e from the expected similarities than those exposed to repeated coalescence treatments and having lo w er ratio of river inoculum, r espectiv el y.On av er a ge, coalesced comm unities sho w ed greater similarity to sea ( β Bray-Curtis : 0.39) than to river ( β Bray-Curtis : 0.17) par ent comm unities (Fig. 4 B).

Discussion
In this study, we mimicked estuarine conditions by mixing a subar ctic freshw ater river community with a brackish water community from the Gulf of Bothnia and assessed the outcome of different mixing scenarios.We observed asymmetrical community coalescence outcomes as coalesced communities were generally shifted to w ar ds the sea parent community, which was also gen-er all y less impacted by the effect of environmental coalescence (i.e ., en vir onmental filtering).Comm unity coalescence incr eased community stability and most likely promoted competitive interactions with the introduced species, leading to a stabilizing effect by negativ e-feedbac k loops.Ov er all, the pr edictability of coalescence outcomes was greater when sea microbes dominated the final community, and this predictability increased when communities were repeatedly mixed.

Compositional dynamics imposed by coalescences
The sampled water bodies ar e c har acterized by oligotrophic conditions (Andersson et al. 1996, Wasmund et al. 2001, Wikner and Andersson 2012 ).Specifically, our inocula originated from phosphorus-and nitrogen-limited river and sea habitats, respectiv el y.In suc h oligotr ophic envir onments, we expect species to be under higher stress than in nutrient-rich environments (Ornolfsdottir 2004 ).
Riv er comm unities subjected to envir onmental coalescence suffered a four times greater taxa loss (8% of riverine OTUs), compared to the sea microbiome (2% of marine O TUs).T his suggests , in line with Cloern et al. ( 2017 ) and Rocca et al. ( 2020 ), that sea micr oeukaryotes ar e better ada pted to the ne w envir onment imposed by habitat mixing, pr obabl y due to their br ac kish origin, making them more tolerant to saline conditions than freshwater species.Ho w e v er, most diatoms, the gr oup that suffer ed the most from the biotic effects of community coalescence, originated from sea communities.
In community coalescence treatments, unequal mixing ratios of river and sea comm unities r esulted in contr asting algal biomass, wherein primary producers decreased in sea-dominated coalesced comm unities, while incr eased in riv er-dominated micr ocosms ov er time.A possible explanation for this phenomenon is that the more saline mixed medium causes riverine algal biomass to decline (i.e.filtered by the envir onment), whic h leads to the opening of niches that the more salt tolerant sea algae can occupy and utilize the ri ver-deri ved high nitrogen supply for their gr owth.Ne v ertheless, it seems that c hanges in water conditions exert minimal influence on microeukaryotes in general, as evidenced by the low percentages of species loss during environmental coalescences .T his might be the consequence of the small changes in salinity being within the tolerance range of microeukaryotes, or due to complex ecological interactions where changes in salinity due to habitat mixing influence heterotrophic microeukaryotes .For example , the decline of certain microbes , as discussed abo ve , opens nic hes and r eleases or ganic matter for the microbial loop, supporting bacterial growth and thereby bacterivor ous micr oeukaryotes (Stefanidou et al. 2018 ).We can speculate that this process can further be promoted by the ele v ated photosynthesis (observed in river-dominated coalesced communities, see e.g.Supplementary Fig. S4 ) that might have increased pH (not measur ed her ein) and in turn r eleased copr ecipitated P into the water, as evidenced by the incr eased TDP le v els in coalesced communities.In addition to environmental filtering, enhanced biotic inter actions (e.g.diatom-c hytrids) (Vass et al. 2022 ), as well as the unexpected bacterial growth in the supplied medium, may ha ve pla yed a r ele v ant r ole in the in sea-dominated coalesced communities, contributing to the species loss and the observed trend of declining biomass of primary producers (e.g.diatoms) in sea-dominated coalesced microcosms (i.e.RC 1:2 /OC 1:2 ), while elevating the abundance of chytrids (parasitic zoosporic fungi).The abundance of bacterial cells in the sea medium supply increased as a result of the lack of complete cell r emov al during medium pr epar ation.This likel y pr ovided an additional food source for gr azers suc h as ciliates and fla gellates during medium r efr eshments.If we hypothesize that this bacterial gr owth r elaxed competition among grazers such as ciliates, w e w ould expect a decrease in negative cohesion and an increasing trend in abundance of Ciliophora taxa across treatments with sea dominance .T his , ho w e v er, was not the case.Instead, ciliates exhibited a significantl y gr eater incr ease in OC tr eatment compar ed to RC tr eatments, whic h wer e exposed to medium exc hange fr om the affected sea medium supply to a greater extent.Nevertheless, future studies would clearly benefit from the simultaneous investigation of both bacterial and microeukaryotic communities in coalescence experiments to r e v eal the particular effects of trophic interactions.
The high number of unique microeukaryotes in coalesced communities suggests and supports an earlier finding that r ar e micr obial taxa emerge during mixing events (Rocca et al. 2020 ).Such phenomena are most likely attributed to the selective adv anta ge of certain phenotypes of these microbes under the new coalesced conditions, as well as the earlier described potential decline of certain microbes that opens niches and supports the establishment of emerging taxa.This explanation is also in line with the incr eased comm unity stability (i.e.ele v ated fr action of competitiv e inter actions) observ ed in the environmental coalescence treatments.

Coalescence influences community stability
Community stability can be inferred from numerous community properties (Shade et al. 2012 ).Here, we approached community stability from the point of community cohesion, a metric that estimates the connectivity of microbial communities that stemming from biotic associations (Herren and McMahon 2017 ).As the authors highlight, taxa associations arise from biotic interactions and environmental drivers.Since the results of environmental coalescence treatments suggest low le v el of species loss (i.e.only 2%-8%), we may assume a strong support for competi-tiv e inter actions alone when negativ e cohesion emer ged.Positiv e cohesion can be indicative of both facilitative interactions and envir onmental sync hr on y, and these two cannot be disentangled in our present study.Nevertheless, the ratio of negative and positive cohesion allo w ed us to infer community stability of our observ ed comm unities, giv en that the cohesion v alues ar e indicativ e of negative-and positiv e-feedbac k loops, pr omoting or r educing comm unity stability, r espectiv el y (Mitri and Ric hard Foster 2013, Coyte et al. 2015, Herren and McMahon 2017 ).
Although our findings suggest gr eater ov er all dominance of facilitativ e inter actions and/or the influence of environmental sync hr on y (that is, the dominance of positive cohesion) across treatments, such dominance was limited by coalescence treatments, ele v ating the importance of competitive interactions that tend to be mor e e vident in microbial communities (Foster and Bell 2012 ).The weakened dominance of facilitativ e inter actions could potentially be attributed to disappearing reciprocal benefits (e.g.metabolic cross-feeding), since spatial structuring, that has similar effect, are unlikely in our microcosms (Harcombe 2010 ).In such scenario, the importance of ecological coselection, a phenomenon which aids members of a community to recruit one another, can be diminished and dominant taxa could not invade another community on their own, successfully (Diaz-Colunga et al. 2022 ).Although this reasoning is experimentally not tested her ein, the incr eased le v els of the inv erse Simpson's index in r epeatedl y coalesced comm unities (see e.g.Supplementary Fig. S6 ) may suggest such a phenomenon as it indicates mechanisms that counteract dominance .T his might also explain why numerous micr oeukaryotes, suc h as ciliates and parasitic fungi, could elevate their abundances, following coalescence.This and other processes generated by environmental coalescence could have provided avenues for the introduction of additional species and/or the emergence of rare taxa that triggered competition to a greater extent and by doing so, leading communities towards greater stability.The driving mechanism behind this, as introduced earlier, originates from the increased number of negativ e-feedbac k loops which dampen the destabilizing effect of facilitative interactions that would otherwise lead to species loss.Our diversity estimates can support this reasoning as taxa richness increased in the coalesced comm unities, particularl y in those that experienced r epeated coalescence e v ents, adding further e vidence for a species maxim um of micr oeukaryotes in br ac kish conditions (Filker et al. 2019, Tee et al. 2021 ).
Ov er all, our findings that community coalescence in estuaries str engthens micr oeukaryotic comm unity stability by incr easing the amount of competitions supports the notion that dampening the proportion of positive-feedback loops leads to e v en gr eater stability in microbial communities (Coyte et al. 2015 ), but questions May's ( 1972 ) and Coyte et al.'s ( 2015 ) work on the destabilizing effect of increasing species diversity.The ground truth, howe v er, most pr obabl y lies in between, as species div ersity has been found to increase overall ecosystem stability when diversity is low, and decrease it when it is high (Pennekamp et al. 2018 ).
The composition of the coalesced communities with greater mixing ratio of the sea parent community generated greater predictabilities, suggesting that the predictability of community coalescence outcomes is significantly constrained in asymmetrical coalescence and is influenced by the e v entual dominance of one par ent comm unity.Ne v ertheless, this pr edictability can be further enhanced as the frequency of mixing increases (i.e.repeatedly colliding comm unities).Lec hón-Alonso et al.'s ( 2021 ) sim ulation study suggested that communities experiencing repeated mixing e v ents should gr aduall y shift from competitive to w ar ds more fa-cilitativ e comm unities, whic h we did not find support for in this 16-day long study.Instead, regardless of the frequency of coalescence e v ents (i.e.one-time v ersus r epeated), our coalesced comm unities became mor e competitiv e than their par ent comm unities.

Conclusion
Ov er all, the composition of coalesced communities and the fate of par ent comm unity members ar e gr eatl y influenced by the mixing pr oportion of par ent comm unities, and to a lesser extent the temporal dynamics of community coalescence (one-time versus regular exchange).Our finding that community coalescence increases micr oeukaryotic div ersity and pr omotes stability should be tested on microbial communities originating from other climatic regions and estuary systems with greater differences in salinity between endmembers to determine how these results can be generalized acr oss estuaries.Additionall y, we belie v e that assessing the effects of community stability on coalescence outcomes presents an intriguing avenue for future research.Although the more stable parent community dominated the final assemblages, which might have led to the observed asymmetrical outcomes, our study, with its single pair of communities, does not provide definitive evidence to either support or reject the notion that community stability influences coalescence outcomes.
Understanding the outcomes of community coalescence and the fate of microbes in their mixed environment is essential to understand and model biodiversity and associated functionality.A changed climate or influence of pollutants could modify coalescence outcomes (Vass et al. 2021(Vass et al. , 2024 ) ), and e v en v ariation in weather conditions trigger mor e fr equent and intense mixing scenarios (e.g.flooding and soil runoff into str eams/riv ers in response to heavy rainfalls) (Mansour et al. 2018 ).These processes will ine vitabl y impact all features of estuarine ecosystems, including diversity, composition, function, and its capability to respond to various disturbances (Rocca et al. 2021 ).
indicating n umerous positi v e-feedbac k loops that lead to low stability(Herren and McMahon 2017 , Hernandez et

F
igure 2. (A) Microeukary otic comm unity compositions acr oss par ent communities and coalescence treatments.Stress value is shown on the upper right corner.(B) Community stabilities based on the ratio of negati ve:positi ve cohesion (Herren and McMahon 2017 ) across parent communities and treatments.Significant ( P < .05)differences in community stability across samples and mixing ratios are represented b y lo w er case and italicized letters, r espectiv el y.N = 5 for each type of sample and tr eatment.Err or bars indicate standard deviations.

Figure 3 .
Figure3.Relative abundances ( > 0.5%) of microeukaryotes in the coalesced communities across different community coalescence treatments with three mixing ratios (river:sea).OTUs of coalesced communities showing significant ( p FDR.adj < 0.05) increase or decrease in taxa abundance due to biotic component of community coalescence, compared to their parent communities, were identified by differential abundance analysis, and grouped by higher taxonomic levels for clarity.

Figure 4 .
Figure 4. (A) Predictability of biotic component of community coalescence outcomes increases with the ratio of sea community in the final coalesced communities based on the similarity of the observed and expected communities.All observed communities significantly differ from the expected communities ( P < .001).Significant ( P < .05)differences among treatments are represented by lowercase letters.(B) Similarity of the observed and expected coalesced communities in relation to their parent communities.Expected community similarities were determined by conservative mixing model based on the applied mixing ratio or river and sea parent community (see the section 'Methods' for details).N = 5 for each type of treatment.Error bars indicate standard deviations.